Transform Retail with IBM Big Data Solutions

TechD

New technologies have permanently transformed how customers communicate, interact, research and shop for goods and services. Retail data paired with retail analytics, can assist retailers in understanding and responding with actionable retail insights to the disrupted landscape and changing customer expectations.
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Spotlight

The way businesses collect, analyze, and use data is changingfrom simply looking for and visualizing historical trends, to using advanced mathematical models to examine data in real time and predict what might happen next. Beyond that, the more switched-on companies are also starting to use technology to influence those outcomes, by combining data analytics with business process automation to create what analyst firm Forrester has identified as the Enterprise system of insight1 , technology designed to enable companies to transform into truly data-driven businesses able to listen and react to what their customers tell them through day to day interactions. Understandably, much of this development has been aimed at and led by data scientists, business analysts, and other specialists typically tasked with building data dashboards and applications for end users. However, with more data problems than specialists to solve them, vendors such as TIBCO now provide self-service data analytics and automation toolkits that anyone can use to bridge the gap. These easy to use tools have been widely welcomed, however they are no substitute for specialist knowledge, and the issue remains of where, when, and how best to deploy them to create real business value

OTHER ON-DEMAND WEBINARS

Building a Modern Operational Data Warehouse

tdwi.org

With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.
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Modernize Your Data Architecture to Deliver Oracle as a Service

robin.io

The migration to cloud-based data architectures continues at a rapid pace, including databases and data management. Oracle databases are part of this trend, and during this webinar you will learn how to automate the provisioning and management of Oracle databases so that you can deliver an “as-a-service” experience with 1-click simplicity. Experts will walk you through the process of
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The Software-Defined Data Center: A Foundation for Digital Transformation

tierpoint

As reported in Forbes last year, 73% of companies are planning to move to a fully software-defined data center within two years. A software-defined data center is based on a virtualized environment of compute, storage, networking and security in conjunction with policy-based management and automation. The evolution from a traditional data center architecture to one that is software-defined can take months if not years but can yield immense benefits for the business. Join us for a discussion on the progress toward the fully software-defined data center, including benefits of infrastructure as code and overcoming challenges associated with traditional workflows.
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The Modern Toolkit for Process Excellence

info.minitab.com

See in action, using a real-world use case from manufacturing, the latest toolkit for Process Excellence, powerful analytics and machine learning.How to use the Minitab toolkit to manage projects and analyse data following the Lean Six Sigma DMAIC structured approach.Discover how to power and digitalise your improvement projects and data analysis with best practice methods combined with intuitive tools.Explore how to solve problems and suggest innovations with whatever data you currently have available.Includes helpful examples of the capabilities and uses for Minitab Statistical Software, Companion by Minitab for project execution and tracking Continuous Improvement, and Salford Predictive Modeler Software for predictive analytics and machine learning.
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Spotlight

The way businesses collect, analyze, and use data is changingfrom simply looking for and visualizing historical trends, to using advanced mathematical models to examine data in real time and predict what might happen next. Beyond that, the more switched-on companies are also starting to use technology to influence those outcomes, by combining data analytics with business process automation to create what analyst firm Forrester has identified as the Enterprise system of insight1 , technology designed to enable companies to transform into truly data-driven businesses able to listen and react to what their customers tell them through day to day interactions. Understandably, much of this development has been aimed at and led by data scientists, business analysts, and other specialists typically tasked with building data dashboards and applications for end users. However, with more data problems than specialists to solve them, vendors such as TIBCO now provide self-service data analytics and automation toolkits that anyone can use to bridge the gap. These easy to use tools have been widely welcomed, however they are no substitute for specialist knowledge, and the issue remains of where, when, and how best to deploy them to create real business value

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